The present invention relates to a medical image processing apparatus, method, and program for extracting a left ventricular region, a right ventricular region, and the like from medical image data containing an image of a heart.
Heretofore, various methods have been proposed for extracting, for example, a left ventricular region of a heart from a medical image, such as a computed tomography (CT) image, a magnetic resonance imaging (MRI) image, or an ultrasound image (refer to H. A. Kirisli et al., “Fully automatic cardiac segmentation from 3D CTA data: a multi-atlas based approach”, Proc. SPIE, Vol. 7623, Medical Imaging 2010: Image Processing, pp. 762305-1-762305-9, 2010, J. Ulén et al., “Optimization for Multi-Region Segmentation of Cardiac MRI”, STACOM'11 Proceedings of the Second International Workshop on Statistical Atlases and Computational Models of the Heart: Imaging and Modelling Challenges, pp. 1-10, 2011, and Y. Zheng et al., “Four-Chamber Heart Modeling and Automatic Segmentation for 3D Cardiac CT Volumes Using Marginal Space Learning and Steerable Features”, IEEE Transactions on Medical Imaging, Vol. 27, No. 11, pp. 1-14, 2008).
Further, four-dimensional medical images in which a time axis is added to the spatial three-dimensions have become obtainable in recent years, and more specifically, a plurality of three-dimensional medical images has become obtainable during one heartbeat. Analyzing a plurality of such cardiac three-dimensional images allows further analysis of cardiac functions, including ejection fraction, end-diastolic volume, end-systolic volume, stroke volume, cardiac output, and cardiac mass.
A heart has four rooms, and the automatic extraction of a left ventricle, which is supposed to be clinically the most important, has been most intensively studied, but now the right ventricle, and left and right atriums have also become the subject of research. Improving the accuracy of automatic extraction of these rooms will be able to reduce the work burden on the doctors for correction.